In this research, we propose to conduct diagnostic and
predictive analysis about the key factors and consequences of urban
population relocation. To achieve this goal, urban simulation models
extract the urban development trends as land use change patterns from
a variety of data sources. The results are treated as part of urban big
data with other information such as population change and economic
conditions. Multiple data mining methods are deployed on this data to
analyze nonlinear relationships between parameters. The result
determines the driving force of population relocation with respect to
urban sprawl and urban sustainability and their related parameters.
This work sets the stage for developing a comprehensive urban
simulation model for catering to specific questions by targeted users. It
contributes towards achieving sustainability as a whole.